Hölder exponent spectra for human gait

Scafetta, Nicola; Griffin, Lori A.; West, Bruce J.

doi:10.1016/s0378-4371(03)00527-2

Cited by 84 publications

(86 citation statements)

References 22 publications

(33 reference statements)

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“…3 for the experimental data, for details see Ref. [7]. The figure shows that the SCPG model is able to generate artificial stride interval time series with statistical properties similar to the fractal and multifractal behavior of real data.…”

Section: Simulated Stride Interval Gaitmentioning

confidence: 86%

“…More details regarding the collection of data can be found at Physionet [11] from where the data were downloaded and in Ref. [7,12].…”

Section: Human Gait Analysismentioning

confidence: 99%

“…Subsequent studies by West and Griffin [3,4] supported the conclusion that the human gait time series is fractal. However, more recently it was determined that these time series, rather than being monofractal, are weakly multifractal [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…The time series is sometimes non-stationary and its fractal variability changes in the different gait mode regimes [7]. In particular, the persistence, as well as the multifractality of the stride interval time series, tends to increase for both slow and fast pace, above that of the normal paces.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear dynamical model of human gait

2003

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We present a nonlinear stochastic model of the human gait control system in a variety of gait regimes. The stride interval time series in normal human gait is characterized by slightly multifractal fluctuations. The fractal nature of the fluctuations become more pronounced under both an increase and decrease in the average gait. Moreover, the long-range memory in these fluctuations is lost when the gait is keyed on a metronome. The human locomotion is controlled by a network of neurons capable of producing a correlated syncopated output. The central nervous system is coupled to the motocontrol system, and together they control the locomotion of the gait cycle itself. The metronomic gait is simulated by a forced nonlinear oscillator with a periodic external force associated with the conscious act of walking in a particular way.

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Section: Simulated Stride Interval Gaitmentioning

confidence: 86%

“…More details regarding the collection of data can be found at Physionet [11] from where the data were downloaded and in Ref. [7,12].…”

Section: Human Gait Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Nonlinear dynamical model of human gait

2003

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“…They studied the dynamical changes of human gait, connected with various diseases [13][14][15][16], the increasing instability of gait in elderly people [13,[16][17][18], presence of long-range correlations in stride interval fluctuations [19,20], stride-to-stride variability and its temporal organization in children [21]. Walking indeed constitutes a complex process which we only recently started to understand through the application of non-linear data processing techniques [12,[22][23][24][25][26][27].…”

Section: Human Gait Dynamicsmentioning

confidence: 99%

Statistical quantifiers of memory for an analysis of human brain and neuro-system diseases

Demin

Yulmetyev

Panischev

et al. 2008

Physica A: Statistical Mechanics and its Applications

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On the basis of a memory function formalism for correlation functions of time series we investigate statistical memory effects by the use of appropriate spectral and relaxation parameters of measured stochastic data for neuro-system diseases. In particular, we study the dynamics of the walk of a patient who suffers from Parkinson's disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), and compare against the data of healthy people (CO -control group). We employ an analytical method which is able to characterize the stochastic properties of stride-to-stride variations of gait cycle timing. Our results allow us to estimate quantitatively a few human locomotion function abnormalities occurring in the human brain and in the central nervous system (CNS). Particularly, the patient's gait dynamics are characterized by an increased memory behavior together with sizable fluctuations as compared with the locomotion dynamics of healthy patients. Moreover, we complement our findings with peculiar features as detected in phase-space portraits and spectral characteristics for the different data sets (PD, HD, ALS and healthy people). The evaluation of statistical quantifiers of the memory function is shown to provide a useful toolkit which can be put to work to identify various abnormalities of locomotion dynamics. Moreover, it allows one to diagnose qualitatively and quantitatively serious brain and central nervous system diseases.

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Fractal Physiology, Complexity, and the Fractional Calculus

West

2006

Fractals, Diffusion, and Relaxation in Disordered Complex Systems

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Hölder exponent spectra for human gait

Cited by 84 publications

References 22 publications

Nonlinear dynamical model of human gait

Nonlinear dynamical model of human gait

Statistical quantifiers of memory for an analysis of human brain and neuro-system diseases

Fractal Physiology, Complexity, and the Fractional Calculus

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